Scalable Probabilistic Models for Face and Speaker Recognition
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In this paper, we present a principled SVM based speaker verification system. A general approach to compute two sequences of frames is developed that enables the use of any kernel at the frame level. An extension of this approach using the Max operator is ...
In this paper, a fast and effective multi-view face tracking algorithm with head pose estimation is introduced. For modeling the face pose we employ a tree of boosted classifiers built using either Haar-like filters or Gauss filters. A first classifier ext ...
This paper present a principled SVM based speaker verification system. We propose a new framework and a new sequence kernel that can make use of any Mercer kernel at the frame level. An extension of the sequence kernel based on the Max operator is also pro ...
This paper proposes a discriminative approach to template-based keyword detection. We introduce a method to learn the distance used to compare acoustic frames, a crucial element for template matching approaches. The proposed algorithm estimates the distanc ...
This paper proposes a discriminative approach to template-based keyword detection. We introduce a method to learn the distance used to compare acoustic frames, a crucial element for template matching approaches. The proposed algorithm estimates the distanc ...
The principal objective of this thesis is to investigate approaches toward a robust automatic face authentication (AFA) system in weakly constrained environments. In this context, we develop new algorithms based on local features and generative models. In ...
This paper presents a tight lower bound on the time complexity of indulgent consensus algorithms, i.e., consensus algorithms that use unreliable failure detectors. We state and prove our tight lower bound in the unifying framework of round-by-round fault d ...
This paper present a principled SVM based speaker verification system. We propose a new framework and a new sequence kernel that can make use of any Mercer kernel at the frame level. An extension of the sequence kernel based on the Max operator is also pro ...
We present a method for combining a number of Support Vector Machines trained independently in the eigenface space and we apply it to face class modeling. We first train several ...
In this paper we present a study of automatic speech recognition systems using context-dependent phonemes and graphemes as sub-word units based on the conventional HMM/GMM system as well as tandem system. Experimental studies conducted on three different c ...
